Kimi k1.5: Next-Gen LLM with RL for Multimodal Reasoning | Benchmark Performance

Kimi k1.5: Next-Gen LLM with RL for Multimodal Reasoning | Benchmark Performance

ByAmar Jaiswal

Reinforcement learning (RL) has revolutionized AI at its core by enabling models to learn iteratively through interaction and feedback. When applied to large language models (LLMs), RL unlocks new opportunities for dealing with tasks involving sophisticated reasoning, e.g., math problem-solving, programming, and multimodal data interpretation. Classical approaches are greatly dependent on pretraining with massive static…

DeepSeek-R1 vs OpenAI o1: 2025 AI Showdown — Math, Coding & Cost Analysis

DeepSeek-R1 vs OpenAI o1: 2025 AI Showdown — Math, Coding & Cost Analysis

ByAmar Jaiswal

Benchmark DeepSeek-R1 OpenAI o1-1217 AIME 2024 79.8% 79.2% Codeforces 96.3 percentile 89 percentile MATH-500 97.3% 96.4% SWE-bench Verified 49.2% 48.9% GPQA Diamond 71.5% 75.7% MMLU 90.8% 91.8% Key Takeaways: While both DeepSeek-R1 and OpenAI o1 exhibit impressive capabilities, they also have limitations:

Multi-level Deep Q-Networks

Riding the Bitcoin Wave with Multi-level Deep Q-Networks

ByAmar Jaiswal

From my experience in the trading world, I can tell you that staying ahead of the curve is key. And in the fast-paced world of Bitcoin, that means exploring new tools and strategies. That’s why I’ve been diving into Multi-level Deep Q-Networks (MDQNs). They offer a unique approach to tackling the complexities of cryptocurrency trading….

CrewAi

CrewAI – The AI Framework That’s Changing the Game

ByAmar Jaiswal

Artificial Intelligence (AI) has evolved from a concept that was once pure speculation to becoming a reality today, changing various industries and ways of approaching complex problems. Among the latest breakthroughs in AI technology is CrewAI, an advanced framework designed to coordinate autonomous AI agents to operate as a unified group. This article will outline the nature of CrewAI, its significance, possible applications, and what it may mean for the future. At the end, readers will gain an understanding of the transformative nature of CrewAI and how to apply it to keep pace with the relentless evolution of AI. CrewAI is an open-source, Python-based multi-agent orchestration framework that enables AI agents to collaborate seamlessly, much like a human team. Developed by João…

Algorithmic Trading
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10 AI Agent Tools That Are Reshaping the Algorithmic trading Industry in 2025

ByAmar Jaiswal

Algorithmic trading has entered a thrilling new chapter: AI-driven agents now tackle vast data streams with near-human intuition and machine-level speed. These cutting-edge tools are rewriting the rules of engagement in both cryptocurrency and traditional markets, liberating traders from endless chart-watching and code-heavy processes. If you’ve ever dreamt of orchestrating a symphony of bots to…

Smart Contract

Transforming M&A Transactions: How Smart Contracts Simplify and Streamline Deals

ByAmar Jaiswal

Mergers and Acquisitions (M&A) are complex transactions that involve multiple stakeholders, extensive documentation, and rigorous regulatory scrutiny. The intricacies and high stakes of M&A can lead to significant challenges, which innovative technologies like smart contracts can help mitigate. Smart contracts, powered by blockchain technology, provide a promising avenue for streamlining M&A processes through automation and…

LLaVA-o1: Redefining Visual Language Model Reasoning

LLaVA-o1: Transforming How We Think with Visual Language Models (VLMs)

ByAmar Jaiswal

The performance of Visual Language Models (VLMs) has often lagged behind due to a lack of systematic approaches. This limitation becomes especially pronounced in tasks requiring complex reasoning, such as multimodal question answering, scientific diagram interpretation, or logical inference with visual inputs. The introduction of LLaVA-o1 represents a significant leap forward. This innovative model tackles…

Six small autonomous robots with varying designs displayed in a futuristic showroom with a large screen showing 'Agentic Mesh: Pioneering the Future of Autonomous Agent Ecosystems

Agentic Mesh: Pioneering the Future of Autonomous Agent Ecosystems

ByAmar Jaiswal

As the capabilities of artificial intelligence continue to grow, autonomous agents—AI-driven entities capable of independently performing complex tasks—are increasingly integrated into various sectors. These agents promise improved efficiency, continuous operation, and the potential to automate vast swathes of routine and complex tasks alike. However, as more agents join this digital ecosystem, managing and coordinating these…

Infographic showing the technical architecture and components of Mixture of Experts (MoE) system with a central MOE logo surrounded by various interconnected modules and explanatory diagrams

Mixture of Experts (MoE): Inside Modern LLM Architectures

ByAmar Jaiswal

In recent years, the rise of Mixture of Experts (MoE) architecture has reshaped large language models (LLMs), enabling advancements in computational efficiency and scalability. Originally proposed by researchers like Noam Shazeer, MoE architecture leverages specialized “experts” for processing different types of data inputs. This approach has proven valuable for scaling models while managing computational demands…

Book cover showing a cartoon robot holding a traffic light on a yellow crosswalk against a dark blue cityscape background

Implementing RAG Systems with Unstructured Data: A Comprehensive Guide

ByAmar Jaiswal

In today’s digital landscape, organizations face a growing challenge: extracting meaningful insights from vast repositories of unstructured data. While Large Language Models (LLMs) have revolutionized how we process information, their true potential is unlocked when combined with Retrieval-jjAugmented Generation (RAG) systems. This guide explores how modern RAG implementations are evolving beyond simple text documents to…